Correlation Between General Mills and Campbell Soup
Can any of the company-specific risk be diversified away by investing in both General Mills and Campbell Soup at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining General Mills and Campbell Soup into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Mills and Campbell Soup, you can compare the effects of market volatilities on General Mills and Campbell Soup and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in General Mills with a short position of Campbell Soup. Check out your portfolio center. Please also check ongoing floating volatility patterns of General Mills and Campbell Soup.
Diversification Opportunities for General Mills and Campbell Soup
0.2 | Correlation Coefficient |
Modest diversification
The 3 months correlation between General and Campbell is 0.2. Overlapping area represents the amount of risk that can be diversified away by holding General Mills and Campbell Soup in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Campbell Soup and General Mills is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on General Mills are associated (or correlated) with Campbell Soup. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Campbell Soup has no effect on the direction of General Mills i.e., General Mills and Campbell Soup go up and down completely randomly.
Pair Corralation between General Mills and Campbell Soup
Considering the 90-day investment horizon General Mills is expected to generate 1.55 times less return on investment than Campbell Soup. But when comparing it to its historical volatility, General Mills is 1.23 times less risky than Campbell Soup. It trades about 0.04 of its potential returns per unit of risk. Campbell Soup is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 4,097 in Campbell Soup on December 29, 2023 and sell it today you would earn a total of 348.00 from holding Campbell Soup or generate 8.49% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
General Mills vs. Campbell Soup
Performance |
Timeline |
General Mills |
Campbell Soup |
General Mills and Campbell Soup Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with General Mills and Campbell Soup
The main advantage of trading using opposite General Mills and Campbell Soup positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if General Mills position performs unexpectedly, Campbell Soup can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Campbell Soup will offset losses from the drop in Campbell Soup's long position.General Mills vs. Bunge Limited | General Mills vs. Altria Group | General Mills vs. Philip Morris International | General Mills vs. Everest Consolidator Acquisition |
Campbell Soup vs. Bunge Limited | Campbell Soup vs. Altria Group | Campbell Soup vs. Philip Morris International | Campbell Soup vs. Everest Consolidator Acquisition |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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